Senior Machine Learning Platform Engineer

Sourced from victra.careers

Klaviyo is hiring a Senior Machine Learning Platform Engineer to build the core platforms, tools, and infrastructure that ML and AI engineers rely on to create advanced agents and models. This backend-heavy individual contributor role drives model training and deployment, feature data standardization, and reliable scaling at massive data and traffic scale. You will lead technical execution, conduct code and design reviews, and partner with product, ML, data science, and infrastructure teams. The role is based in Boston.

• Enable AI/ML teams to ship models and ML-powered features faster, more safely, and more reliably
• Evolve ML and LLM platform architecture for building, evaluating, and operating production ML systems
• Improve reliability, observability, and cost efficiency of ML training and inference workloads
• Architect and scale systems for feature storage and real-time retrieval for training and inference datasets
• Lead technical execution, conduct code and design reviews, and author high-impact code
• Mentor engineers and drive architectural design and technical direction
• Partner with product and engineering leaders to define the ML Platform roadmap

• 7+ years of experience as a software engineer, ML platform engineer, or similar, building backend or distributed systems
• Demonstrated experience designing and launching AI/ML systems in production at scale
• Strong proficiency in Python (or a similar backend language such as Go, Java, or Scala)
• Experience with cloud infrastructure and platform fundamentals (AWS, Kubernetes)
• Familiarity with data-intensive systems: streaming or batch processing, data modeling, and large-scale data (Spark, Ray Data)
• Comfortable collaborating with cross-functional technical partners (ML, product, infra, security)
• Strong communication skills and a track record of driving technical excellence across teams

• Experience with Ray Jobs and Ray Tune
• Experience with LLM platform architecture
• Prior MLOps experience in high-scale environments